Description
Job Summary
We are seeking a highly skilled AI/ML Solutions Architect to lead the design, development, and deployment of advanced artificial intelligence and machine learning solutions supporting mission-critical government and national security programs. This role partners closely with data scientists, software engineers, cloud architects, and mission stakeholders to translate complex operational requirements into scalable, secure, and high-performance AI/ML architectures.
The ideal candidate combines deep technical expertise with a strategic mindset and has experience architecting end-to-end AI/ML solutions operating in classified cloud environments. This role spans the full ML lifecycle—from data ingestion and model training to deployment, monitoring, and governance—while ensuring compliance with DoD and Intelligence Community security standards. Strong communication skills, architectural leadership, and a commitment to secure, reliable mission outcomes are essential.
Key Responsibilities
Architect and guide end-to-end AI/ML solutions in support of mission-critical programs
Design, integrate, and optimize full-lifecycle ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
Ensure AI/ML systems meet federal security, compliance, and accreditation requirements
Collaborate with cross-functional technical teams and mission stakeholders to align solutions with operational needs
Evaluate emerging AI/ML technologies and develop technical roadmaps for long-term scalability and reliability
Support customer-facing technical engagements and clearly communicate complex AI/ML concepts to diverse audiences
Requirements
Required Experience
Bachelor’s degree in Computer Science, Engineering, Physics, Statistics, Mathematics, or a related field
5+ years of professional experience in AI/ML engineering, data science, or MLOps within cloud environments
U.S. citizenship with the ability to obtain and maintain a TS/SCI security clearance
Demonstrated experience designing and operating end-to-end AI/ML pipelines in classified environments
Experience operationalizing ML models and data pipelines across air-gapped, hybrid, and cloud infrastructures
Hands-on experience with at least one major AI/ML platform (e.g., Azure Machine Learning, AWS SageMaker, Kubeflow on Kubernetes)
Proven experience working with structured and unstructured data and managing the ML model lifecycle
Experience collaborating with multidisciplinary teams and supporting mission stakeholders
Required Skills
Deep knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and data tools (Spark, Pandas, Kafka)
Strong understanding of AI/ML architecture patterns and MLOps practices, including CI/CD, deployment, monitoring, and governance
Proficiency in Python for AI/ML development; familiarity with Java, Go, or C++ is a plus
Expertise with cloud-native and container technologies (Kubernetes, Docker, serverless architectures)
Understanding of cloud security principles, zero-trust architectures, and secure system design
Ability to translate mission requirements into technical AI/ML architectures
Excellent written and verbal communication skills, including briefing senior stakeholders
Desired Skills
Active TS/SCI clearance
Professional certifications such as cloud solutions architect or AI/ML specialty certifications
Experience with advanced ML domains (e.g., federated learning, reinforcement learning, LLM fine-tuning, vector databases, retrieval-augmented generation)
Familiarity with DoD and Intelligence Community data environments and RMF accreditation processes
Understanding of secure data enclaves, cross-domain solutions, and zero-trust implementations
Experience with model interpretability, bias mitigation, and Responsible AI practices
